Abstract
Internet of Everything (IoE) devices have different operation principles, which weakens the network scalability and data interoperability. Virtualization is an economic way of solving this problem. The data-collected by different vendors' sensors-can share the same computing program encapsulated by the Virtual Machine (VM), thus neglecting the physical-layer difference. To eliminate the extreme cost and long delay of transferring VMs to the remote cloud, the Edge Device (ED) preliminary processes its running VMs. Currently, the recycling of IoE devices become a major dilemma for individuals, since it is not simply a matter of concern for environmental damage or a solution to an environmental problem. Therefore, the sustainable strategy for recycling EDs is an important way to safeguard the network sustainability. To improve the recycling efficiency, most of the EDs should be upgraded simultaneously during one batch by migrating their running VMs to others for the service continuity. We investigate the least upgrade batch for recycling EDs in IoE networks. A two-step algorithm called MSBP (Minimized upgrade batch VM Scheduling and Bandwidth Planning) is designed to minimize the number of upgrade batches. Because migrating VM brings the bandwidth consumption along trajectories, MSBP has two strategies-Shortest Trajectory First (STF) and Least Bandwidth Utilization First (LBUF)-of allocating bandwidth and trajectories. The simulation results show that: 1) MSBP has the optimal recycling efficiency (least number of upgrade batches) for EDs; 2) LBUF more effectively mitigates the phenomenon where VM migration trajectories compete for the common link bandwidth, thus achieving a lower negative impact of path contention level on the recycling efficiency; 3) the battery power is not exhausted for the ED functioned as the sensor head of data transferring, thus prolonging the network lifetime. In summary, our solution well improves the network, social, economic and ecological sustainability.
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